Using wavelet transform (WT) for increasing signal-to-noise ratio (SNR) of discrete-time signals corrupted by additive noise is explained and compared with some other techniques (averaging, frequency filtration, correlation). Signal processing for de-noising is applied to basic periodical signals and repeated transients (in nondestructive ultrasonic testing of welds, where presence of flaws sho...

In order to preserve the integrity of edge and detail information in the underwater image, a NSCT de-noising method based on Non-local means with modified parameter is proposed. Since NSCT has the feature of translation invariance, it is used to decompose the underwater image in multi-scale and multi-direction. For the noise and detail information are normally distributed in the high frequency ...

This paper introduces the Laplace algorithm for de-noising in the cepstrum domain with applications to speech recognition. Our method uses Gaussian mixture priors for clean speech and noise cepstra and assumes that speech and noise mix linearly in the spectrum domain. The Laplace algorithm involves two steps (a) computing the posterior mode of the observed noisy cepstra and (b) Gaussian approxi...

Recent research has shown that deep neural network is very powerful for object recognition task. However, training the deep neural network with more than two hidden layers is not easy even now because of regularization problem. To overcome such a regularization problem, some techniques like dropout and de-noising were developed. The philosophy behind de-noising is to extract more robust feature...

The Phase-Locked Loop is used to track an incoming signal and provide accurate carrier phase measurements on GPS receivers. However, the PLL performance is affected by the thermal noise and dynamic stress. In order to resolve the conflict between reducing PLL noise and overcoming the dynamic stress, some compromises must be taken in PLL design. This paper proposes a wavelet packet de-noising te...

An image is considered as a collection of information stored as intensities and the occurrence of noises. The occurrence of noise present in the image causes degradation in the quality of the image. The basic idea behind image processing is how we estimate the correct pixel values. Image De-noising is one of the fundamental problems which is faced in image processing and computer vision .There ...

The major problem that wireless communication systems undergo is multipath fading caused by scattering of the transmitted signal. However, we can treat multipath propagation as multiple channels between the transmitter and receiver to improve the signal-to-scattering-noise ratio. While using Single Input Multiple Output (SIMO) systems, the diversity receivers extract multiple signal branches or...

In this paper we proposed a technique to remove eye blink artifact from electroencephalogram (EEG) using lifting wavelet transform (LWT). The LWT has been successfully used in eye blink artifact suppression form the recorded electroencephalography (EEG) signals using a data-adaptive subband filtering approach. The LWT is applied to decompose EEG signal into a finite set of subbands. The energy ...

I introduce a unified approach for de-noising and interpolation of seismic data in the frequency-wavenumber (f-k) domain. First an angular search in the f-k domain is carried out to identify a sparse number of dominant dips, not only using low frequencies but over the whole frequency range. Then, an angular mask function is designed based on the identified dominant dips. The mask function is ut...

EEMD Algorithm is usually applied in noise reduction of rolling bearing signal because of its powerful ability in de-noising. But misjudgment in selecting sensitive IMF exists, it results in the incomplete processing of noise reduction. In order to solve this problem, this paper proposes an improved EEMD algorithm. This algorithm adopts Cloud Similarity Measurement in selecting the sensitive in...